{"id":991,"date":"2019-11-15T18:30:15","date_gmt":"2019-11-15T18:30:15","guid":{"rendered":"http:\/\/janbosch.com\/blog\/?p=991"},"modified":"2019-11-15T18:30:20","modified_gmt":"2019-11-15T18:30:20","slug":"get-your-data-out-of-the-gray-zone","status":"publish","type":"post","link":"https:\/\/janbosch.com\/blog\/index.php\/2019\/11\/15\/get-your-data-out-of-the-gray-zone\/","title":{"rendered":"Get your data out of the gray zone"},"content":{"rendered":"\n
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Photo by Laurenz Blickwedel on Unsplash<\/figcaption><\/figure>\n\n\n\n

Last week, I wrote<\/a> about the different types of use for data that we have available. That led to discussions with various people and I realized that there\u2019s a problem around data that\u2019s very typical in companies that have their roots in embedded systems or mechanical engineering: it\u2019s actually unclear who owns the data from their products.<\/p>\n\n\n\n

Most of the people in R&D that I\u2019ve talked to over the last years\n couldn\u2019t answer the question of who owns the data from their products. \nAnd those that did answer basically assumed the customer to be the \nowner. The first action that every company needs to take is to sort out \nthe status around the data from a legal and practical perspective. It\u2019s \ncritically important to avoid a situation where this is unclear to \ncustomers and to your own staff. When it\u2019s not clear, your staff will \nplay it safe and avoid any use of data in order to avoid causing \ntrouble.<\/p>\n\n\n\n

Once you\u2019ve sorted out the ownership and usage right issues, \nthe next step is to figure out how data could be used for creating value\n for customers. The challenge is that even if you legally own the data, \ncustomers often still feel quite skeptical towards this and it\u2019s \nimportant to be transparent about what data is collected and stored and \nfor what purposes.<\/p>\n\n\n\n

Using data to create value for customers often evolves through five \nstages. The first stage is broadly known and has been used for decades \nin most companies: quality assurance. Most customers have shared data \nfrom their products with the company developing the products in order to\n fix defects and to improve the general performance.<\/p>\n\n\n\n

Once data collection for quality assurance is in place, the R&D \norganization can easily move to the next stage where R&D \neffectiveness data is collected. This can include the usage frequency of\n newly developed features, user experience data or other aspects that \nprovide indications of business value delivered to customers.<\/p>\n\n\n\n

The third stage is where you use the customer\u2019s data to provide \ndata-driven services based solely on that data. Examples of services may\n include general uptime metrics, preventive maintenance, reconfiguration\n times in manufacturing lines and general productivity metrics. The \nadvantage of these data-driven services is that they can run on the \ncustomer\u2019s premises without any concern. One question in this context is\n why the customer would need the company to provide these services as \nthey already have the data themselves. In practice, however, \ninterpreting the data requires a deep understanding of the system, which\n the customer often doesn\u2019t have.<\/p>\n\n\n\n

Once customers are used to the company using their data to deliver \nservices, the next stage is to offer them data-driven services that \ncombine their data with anonymized, aggregated data from the entire \ncustomer base. This is where potential sensitivities concerning \ncompetitive positioning start to play a role and where the company has \nto provide guarantees concerning anonymity and confidentiality. In most \ncases, the starting point is where a number (typically five or more) of \nthe largest customers jointly agree to their data being used for this \npurpose. Many companies use the data available in this stage to offer \nconsultancy services to help their customers improve their performance.<\/p>\n\n\n\n

In the fifth stage, the company offers data-driven services based on \ndata originating from other sources besides its primary customer base. \nThis can include data concerning the customers of their customers, data \nfrom adjacent industries that pertains to this industry in different \nways or general data concerning the economy, currencies, weather, \npolitics or other topics that can have a material effect on your \ncustomers.<\/p>\n\n\n\n

Concluding, if it isn\u2019t clear already, the first step has to be to create clarity and transparency concerning the ownership and usage rights of data coming from your systems deployed at customers. Typically, this requires giving customers something of value that will make it relevant for them to share their data. The use of data often evolves through five stages, as outlined. But start with getting your data out of the gray zone.<\/p>\n\n\n\n

To get more insights earlier, sign up for my newsletter at<\/em>jan@janbosch.com<\/em><\/a> or follow me on<\/em> janbosch.com\/blog<\/em><\/a>, LinkedIn (<\/em>linkedin.com\/in\/janbosch<\/em><\/a>) or Twitter (<\/em>@JanBosch<\/em><\/a>).<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Last week, I wrote about the different types of use for data that we have available. That led to discussions with various people and I realized that there\u2019s a problem around data that\u2019s very typical in companies that have their roots in embedded systems or mechanical engineering: it\u2019s actually unclear who owns the data from … Read more<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"generate_page_header":"","footnotes":""},"categories":[4,8,10],"tags":[],"_links":{"self":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/991"}],"collection":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/comments?post=991"}],"version-history":[{"count":1,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/991\/revisions"}],"predecessor-version":[{"id":993,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/991\/revisions\/993"}],"wp:attachment":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=991"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=991"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=991"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}